Measuring Brand Presence in Generative Engine Optimization: Metrics, Visibility and Validity

Generative Engine Optimization (GEO) is changing the way a brand's visibility on the Internet is measured. While traditional SEO has relied for years on rankings, impressions, clicks and CTR, generative engines present a different scenario: a brand can appear, be cited or influence an artificial intelligence response without the user ever directly visiting its page.A study published in Latitude: Multidisciplinary Research Journal, from Quality Leadership University (QLU), examines precisely this problem. Titled “Medición de la presencia de marca en la optimización para motores generativos: una revisión de alcance sobre métricas y validez” (Measuring brand presence in generative engine optimization: a scoping review of metrics and validity), the work by Romero-Ramos, Lobach, Abreu-Abreu, Castillo-Hernández, García-Cordero and García-Cordero reviews how the presence of brands and sources is currently being measured in generative engines.The main conclusion is especially relevant for SEO and GEO professionals: there are numerous metrics for evaluating AI visibility, but there is still no integrated, psychometrically validated instrument for measuring a brand's generative presence.

What is brand measurement in GEO?

Brand measurement in GEO seeks to determine how visible, present, cited or influential a brand is within the responses generated by artificial intelligence systems.In traditional SEO, a common question is:

What position does my page rank in on Google?

In GEO, the question changes:

Does my brand appear in AI-generated responses, and how does it appear?

The difference is fundamental.A generative system can build a response using information from multiple pages and present that information in synthesized form. As a result, a brand can influence the response even if the user never clicks through to its website.The Latitude study points precisely to this shift from click-based visibility toward presence within synthesized responses.

Why aren’t traditional SEO metrics enough for GEO?

SEO metrics remain important, but they don't fully describe a brand's visibility within generative engines.Traditional indicators include:

• Organic ranking position.
• Impressions.
• Clicks.
• CTR.
• Organic traffic.
• SERP visibility.

In a generative environment, new questions emerge:

• Does the AI mention the brand?
• Does it cite it as a source?
• In what position does the citation appear?
• What information about the brand does it incorporate?
• Does it present it positively, negatively or neutrally?
• How often does it appear?
• Does it also appear alongside competitors?
• Does the response change when the query is repeated?

The study notes that visibility on Google does not necessarily predict visibility within a generative assistant, and that the source-selection logic can vary between engines.

The GEO metrics study published by Latitude

The work was carried out as a scoping review following the Joanna Briggs Institute (JBI) methodology and the PRISMA-ScR guidelines.

Key research data

Feature	Information
Title	Measuring brand presence in generative engine optimization
Study type	Scoping review
Field	Generative Engine Optimization
Primary studies included	23
Period analyzed	2023-2026
Languages	Spanish and English
Methodology	JBI + PRISMA-ScR
Journal	Latitude: Multidisciplinary Research Journal
Volume	2
Issue	24
Pages	23-39
Publication	August 17, 2026
DOI	10.55946/latitude.v2i24.295

The bibliographic data appears on the journal's official page and in the article's PDF.Main academic source: Original article in Latitude

How many studies on GEO measurement were analyzed?

The review included 23 primary studies directly related to measuring presence, visibility, citation or influence in generative engines, plus two reviews used as a conceptual framework.The literature analyzed corresponds mainly to a very recent field. Approximately 94% of the candidate set is concentrated in 2025 and 2026, while the foundational work by Aggarwal et al. initially appeared as a preprint in 2023 and was later published in the KDD proceedings in 2024.Another important point is that the field remains preprint-first: a considerable proportion of the research is disseminated through repositories such as arXiv or SSRN before becoming consolidated in indexed academic publications.

The 7 families of GEO metrics identified

One of the main contributions of the research is the identification of seven families of metrics used to study the presence of sources and brands in generative engines.

1. Appearance and citation

This family measures whether a source or brand is mentioned or cited within a generative response.It is one of the most intuitive metrics:Does the AI mention my brand?However, mere appearance does not necessarily indicate that the brand has a significant influence on the response.

2. Prominence and position

Not all mentions carry the same weight.A brand can appear at the beginning of a response, in a prominent position, or simply as a secondary reference.This family analyzes precisely the position and prominence of the citation or mention.

3. Absorption and influence

This is one of the conceptually most interesting areas of the research.The study differentiates between:Citation: the source is selected or mentioned.Absorption: the content from that source actually contributes to the generated text.This means it is not enough to ask whether an AI cites a page. It is also necessary to study to what extent the information from that source ends up being incorporated into the final response.

4. Position within lists

Some generative queries produce recommendations or lists.For example:

• best hotels.
• best restaurants.
• best SEO tools.
• best universities.
• best products.

In these cases, a brand's position within the generated list can be measured.The research identifies this category as a distinct family of ranking metrics.

5. Stability

Generative engines do not necessarily produce exactly the same response every time.Because of this, a single measurement may be insufficient.The stability family studies the consistency of a brand's presence across different runs and points in time.

6. Sentiment and framing

It is not enough to know whether a brand appears.It also matters how it appears.For example, a brand might be mentioned:

• positively.
• negatively.
• neutrally.
• associated with certain attributes.
• compared unfavorably with competitors.

The review highlights that this signal can show high volatility and, despite this, remains understudied in the academic literature.

7. Citation share

Citation share attempts to determine what proportion of the citations obtained by different brands corresponds to a given company or entity.For example, if a query generates references to five competing brands, one could study what percentage of the citations corresponds to each one.The research points to a particularly interesting gap: although citation share is relevant in professional GEO practice, it is very poorly formalized in the academic literature analyzed.

What other dimensions are emerging in GEO?

Beyond the seven main families, the researchers identify additional dimensions that are gaining relevance.These include:

• verifiable attribution.
• the usefulness of structured data.
• content architecture and topology.
• academic infrastructure.
• robustness.
• manipulation risks.

This shows that GEO measurement is evolving from a simple question—“does my brand appear?”—toward a much more complex model of presence, influence, stability and attribution.

The big problem: there is still no universal GEO metric

This is where the study's main conclusion comes in.Currently there is no universal integrating framework that allows a brand's generative presence to be measured in a standardized way.There are many metrics, benchmarks and experiments, but each piece of research may use:

• different engines.
• different prompts.
• different units of analysis.
• different sample sizes.
• different evaluation criteria.
• different repetition methods.

Because of this, two studies can measure something similar and yet produce results that are not directly comparable.

What unit should be measured in GEO?

Another problem identified by the review is that there is no consensus on the unit of analysis.The research shows an evolution from:URL → document → product → brand/entity → response → agent trajectoryThis represents an important shift compared to traditional SEO.

From the URL to the entity

In SEO we usually analyze a URL.In GEO, the question can be broader:What does the generative system know and say about my brand as an entity?The URL remains relevant because it constitutes a source of information, but it no longer necessarily represents the entire unit of analysis.

From the response to agent behavior

The most recent work is also beginning to study the trajectory of agents capable of navigating and executing actions.This broadens the concept of visibility even further.It is no longer just about:“Did the AI mention me?”but also:“What did the system do after finding my information?”

Variability is one of the biggest problems in GEO measurement

Generative engines have a stochastic component.The same query can generate different responses at different times.Because of this, taking a single measurement can produce an unrepresentative snapshot.The review notes that robust measurement should incorporate repetition and uncertainty modeling. However, only a minority of the studies analyzed systematically control for this variability.

How can this problem be reduced?

A more robust GEO methodology can include:

1. Multiple runs per query.
2. Different prompt formulations.
3. Different languages when relevant.
4. Different points in time.
5. Different generative engines.
6. Recording all responses.
7. Calculating a distribution rather than just a single value.

The research mentions, for example, studies that used five runs per query, hundreds of evaluations, linguistic sensitivity analyses, and measurements taken at different points in time.

Are current GEO metrics valid?

This is probably the study's most important conclusion:there is still not enough evidence to claim that current metrics constitute an integrated, psychometrically validated instrument for measuring a brand's generative presence.The review does not say that the metrics are useless.What it says is something more precise:there are many useful metrics, but their reliability and validity as measurement instruments have yet to be formally demonstrated.

Construct validity and reliability: GEO’s big gap

To understand the problem, two concepts must be distinguished.

What is construct validity?

Construct validity asks whether a metric really measures the concept it claims to measure.For example:If a tool claims to measure “brand presence in AI,” it must be shown that the indicator actually represents that construct.

What is reliability?

Reliability refers to the consistency of the measurement.If a metric is applied repeatedly under comparable conditions, it should produce sufficiently consistent results.The review found that no study in the corpus had subjected its instrument to strict psychometric validation.

GEO measures a lot, but still validates little

One of the best ways to summarize the study's conclusions is:GEO measures a lot, but still validates little.The discipline has produced:

• benchmarks.
• rankings.
• citation metrics.
• prominence indicators.
• stability metrics.
• sentiment analysis.
• influence studies.
• manipulation experiments.

But an instrument that combines these dimensions in a scientifically validated way is still missing.

What does this mean for companies doing GEO?

For a brand, this research has an important practical consequence:a single GEO metric should not be treated as an absolute truth.For example, a brand appearing in 8 out of 10 responses does not automatically mean it has a universally comparable “80% GEO visibility.”The figure depends on:

• the queries.
• the engine used.
• the prompts.
• the date.
• the number of repetitions.
• the competitors included.
• the attribution criteria.
• the methodology used.

Because of this, companies should build their own transparent measurement protocols until a more consolidated scientific standard exists.

How can a brand’s AI presence be measured today?

Although there is still no validated universal index, a company can build an operational measurement system.

Step 1: create a set of queries

Select questions relevant to the brand's category.For example:

• What are the best companies for X?
• What brand do you recommend for X?
• What are the alternatives to X?
• Which company offers X in Panama?
• What is the best solution for X?

Step 2: measure appearance

Record whether the brand appears or not.

Step 3: record position

Determine where the brand appears within the response or list.

Step 4: record the sources

Identify which pages are cited by the engine.

Step 5: analyze the context

Determine what attributes are associated with the brand.

Step 6: measure stability

Repeat the queries and compare results.

Step 7: compare competitors

GEO visibility carries more meaning when analyzed within a competitive context.

Step 8: keep the responses

Save the original responses to be able to compare changes over time.This procedure does not constitute a psychometrically validated instrument, but it does allow for the development of a reproducible and transparent GEO monitoring system.

What relationship exists between SEO and GEO?

SEO and GEO should not necessarily be understood as opposing disciplines.SEO remains important because generative engines need accessible, crawlable and relevant information.However, GEO introduces an additional layer:SEO optimizes the ability to be found; GEO seeks to increase the chances of being understood, cited and used within generative responses.The research analyzed shows precisely that traditional metrics are not enough to explain visibility in generative systems.

What should a brand do to prepare for GEO measurement?

While a scientific standard is being developed, brands can work on several pillars:

Build topical authority

Create content that clearly answers the questions relevant to their sector.

Strengthen brand entities

Maintain consistent information about the company, products, services and associated people.

Improve content structure

Use clear headings, direct answers, tables, lists, structured data and a logical architecture.

Earn external mentions

A brand's presence does not depend solely on its own website.External references can help build the context that generative systems use.

Measure competitors

It is not enough to ask whether the AI mentions our brand.We need to check which brands appear alongside it and how often.

Limitations of the study

The research also acknowledges several limitations.The GEO field is extremely recent and dominated by preprints. In addition, the review was limited to works in Spanish and English and could not verify Scopus due to lack of institutional access.The authors themselves also point out issues related to potential circularity when certain studies use language models as evaluators of their own measurements.Another important aspect is temporal validity: generative systems and their algorithms evolve quickly, so a measurement can lose relevance over time.

What is the future of GEO metrics?

The research points to a clear need: developing and validating a specific index of generative brand presence.That future instrument should integrate several dimensions:

• appearance.
• citation.
• prominence.
• absorption.
• position.
• stability.
• sentiment.
• citation share.
• attribution.
• robustness.
• uncertainty.

In addition, it should demonstrate:

• construct validity.
• reliability.
• reproducibility.
• temporal stability.
• resistance to manipulation.

The goal would not simply be to create another benchmark, but to develop a true scientific measurement instrument.

Conclusion: the next frontier of GEO is measuring correctly

The research published in Latitude raises a fundamental question for the future of generative engine optimization.The problem with GEO is no longer just getting an AI to mention a brand. It is also necessary to demonstrate how to measure that presence reliably.The review of 23 studies reveals a young, dynamic and fragmented field, with seven main families of metrics and growing concern about stability, citation and content absorption.However, an integrated instrument that has scientifically demonstrated its validity and reliability is still missing.Because of this, the next big leap in GEO will probably not be simply developing new techniques to appear in AI responses.It will be creating a methodology capable of demonstrating, in a reproducible way, when a brand is truly present, how it is being represented, and how much it influences generative responses.

Main academic source

Romero-Ramos, N., Lobach, Y., Abreu-Abreu, D., Castillo-Hernández, I., García-Cordero, J. C., & García-Cordero, D. (2026). Medición de la presencia de marca en la optimización para motores generativos: una revisión de alcance sobre métricas y validez. Latitude, 2(24), 23-39.See the original academic article in LatitudeDOI: 10.55946/latitude.v2i24.295.

Other relevant academic sources

Aggarwal et al. — GEO: Generative Engine Optimization

The work by Aggarwal et al. is one of the field's fundamental precedents and was published in the ACM SIGKDD proceedings in 2024. The paper proposes an initial framework for studying optimization for generative engines.DOI of the Aggarwal et al. paper

Alcaraz Martínez and Sulé — GEO review

This review analyzes approaches, metrics and strategies for Generative Engine Optimization and is among the works used as a conceptual framework by the Latitude study.DOI of the Alcaraz Martínez and Sulé review

FAQs about brand measurement in GEO

What is brand presence measurement in GEO?

It is the process of evaluating to what extent a brand appears, is cited, occupies a relevant position, or influences the responses generated by search engines and AI-based assistants.

What does the Latitude review conclude about GEO?

It concludes that there are numerous metrics for studying generative visibility, but that the field remains fragmented and still lacks an integrated, psychometrically validated instrument for measuring a brand's generative presence.

How many studies does the research analyze?

The review includes 23 primary studies published between 2023 and 2026, plus two reviews used as a conceptual framework.

What are the main GEO metrics?

The study identifies seven families: appearance/citation, prominence/position, absorption/influence, list ranking, stability, sentiment/framing and citation share.

What is citation share in GEO?

It is a metric that seeks to determine what proportion of the citations obtained within generative responses corresponds to a brand versus its competitors.

What is the difference between citation and absorption?

Citation indicates that a source has been selected or mentioned. Absorption attempts to determine whether that source's content has actually been incorporated into the generated response.

Why do GEO measurements need to be repeated?

Because generative responses can vary between runs. A single query may not adequately represent a brand's actual visibility. The review recommends considering repetition and uncertainty as important elements of a robust measurement.

Is there a universal GEO index for measuring brands?

No. According to the review analyzed, there is still no integrated instrument specifically validated for measuring a brand's generative presence.

Does a good position on Google guarantee visibility on ChatGPT or Gemini?

Not necessarily. The review notes that the sources cited by generative engines can have limited overlap with those that dominate traditional rankings, and that source selection can vary between systems.

Are SEO and GEO the same thing?

No. SEO focuses mainly on improving visibility in traditional search engines, while GEO studies the optimization and measurement of the presence of content, sources and brands within generative responses.

What should a company measure if it wants to do GEO?

At a minimum, it should record brand appearance, citations, position, context of the mention, competitors, sources used, stability across runs and change over time. For more rigorous results, it is also worth documenting prompts, engines, dates and number of repetitions.

Why is this research important for the future of GEO?

Because it shifts the conversation from “how to appear in an AI” toward a more important scientific question: “how to validly and reliably demonstrate and measure that presence.”